|2. Robotics IJRRD GRAPHICAL ANALYSIS OF Nita Shah|
It is simple for humankind to steadily walk on different terrain, but it is hard to achieve a human-like gait for bipedal walking robots due to their complex dynamics. In general, there are two approaches towards controlling a bipedrobot: static and dynamic walking. In this paper, we demonstrate the dynamic walking approach for controlling a biped robot. In this approach, the walker moves only under the gravitational force...
Keywords: Biped Robots; Passive Walking; Linearization; Switched Conditions; Compass Gait
|3. Robotics IJRRD LOCAL STABILITY ANALYSIS Nita Shah|
The bipedal walking is the main form of locomotion of human kind. The human body is flexible and so it is easy for humankind to steadily walk on the different terrain, howeverbuilding arobot to have a human-like gait is not easy due to the complex dynamics of the walking.In this paper, we focus the passive dynamic bipedal robot (PDBR) which walks only by thepresentof gravity on an inclined ramp, that is, the robotis walking on a ramp in absence of external forces...
Keywords: Bipedal Robot; Passive Walking; Linearization; Switched Conditions; Compass Gait; Orbital Stability; Poincare Map; Phase Space Diagram
|MIT 6.832 Underactuated Robotics, Spring 2009 - MIT OpenCourseWare|
Instructor: Russell Tedrake Robots today move far too conservatively, using control systems that attempt to maintain full control authority at all times. Humans and animals move much more aggressively by routinely executing motions which involve a loss of instantaneous control authority. Controlling nonlinear systems without complete control authority requires methods that can reason about and exploit the natural dynamics of our machines...
Keywords: underactuated robotics; actuated systems; nonlinear dynamics; simple pendulum; optimal control; double integrator; quadratic regulator; Hamilton-Jacobi-Bellman sufficiency; minimum time control; acrobot; cart-pole; partial feedback linearization; energy shaping; policy search; open-loop optimal control; trajectory stabilization; iterative linear quadratic regulator; differential dynamic programming; walking models; rimless wheel; compass gait; kneed compass gait; feedback control; running models; spring-loaded inverted pendulum; Raibert hoppers; motion planning; randomized motion planning; rapidly-exploring randomized trees; probabilistic road maps; feedback motion planning; planning with funnels; linear quadratic regulator; function approximation; state distribution dynamics; state estimation; stochastic optimal control; aircraft; swimming; flapping flight; randomized policy gradient; model-free value methods; temporarl difference learning; Q-learning; actor-critic methods